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Analysis of cell proliferation data.

When estimating the labeling index is of interest, the design of experiments raises a number of methodological questions: How many cells should be scored? How big a difference in labeling index is likely to be detectable? What is the potential effect of low growth fraction on detecting a treatment e...

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Detalles Bibliográficos
Autor principal: Morris, R W
Formato: Texto
Lenguaje:English
Publicado: 1993
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1519430/
https://www.ncbi.nlm.nih.gov/pubmed/8013427
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author Morris, R W
author_facet Morris, R W
author_sort Morris, R W
collection PubMed
description When estimating the labeling index is of interest, the design of experiments raises a number of methodological questions: How many cells should be scored? How big a difference in labeling index is likely to be detectable? What is the potential effect of low growth fraction on detecting a treatment effect? What are appropriate ways of expressing treatment effects on labeling index? Data from two labeling index experiments are used to shed light on these questions. The answers to all questions depend on the level of labeling index under consideration: a low frequency of labeling makes it important to count more cells, but this should not be done at the expense of using fewer animals. Detecting differences between treated and control groups when labeling index is low or when growth fraction is low is difficult, and caution must be used when expressing treatment effect as fold increase when labeling index is small.
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spelling pubmed-15194302006-07-26 Analysis of cell proliferation data. Morris, R W Environ Health Perspect Research Article When estimating the labeling index is of interest, the design of experiments raises a number of methodological questions: How many cells should be scored? How big a difference in labeling index is likely to be detectable? What is the potential effect of low growth fraction on detecting a treatment effect? What are appropriate ways of expressing treatment effects on labeling index? Data from two labeling index experiments are used to shed light on these questions. The answers to all questions depend on the level of labeling index under consideration: a low frequency of labeling makes it important to count more cells, but this should not be done at the expense of using fewer animals. Detecting differences between treated and control groups when labeling index is low or when growth fraction is low is difficult, and caution must be used when expressing treatment effect as fold increase when labeling index is small. 1993-12 /pmc/articles/PMC1519430/ /pubmed/8013427 Text en
spellingShingle Research Article
Morris, R W
Analysis of cell proliferation data.
title Analysis of cell proliferation data.
title_full Analysis of cell proliferation data.
title_fullStr Analysis of cell proliferation data.
title_full_unstemmed Analysis of cell proliferation data.
title_short Analysis of cell proliferation data.
title_sort analysis of cell proliferation data.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1519430/
https://www.ncbi.nlm.nih.gov/pubmed/8013427
work_keys_str_mv AT morrisrw analysisofcellproliferationdata